Model: "functional_1"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) [(None, 150, 150, 3) 0
__________________________________________________________________________________________________
conv2d (Conv2D) (None, 75, 75, 64) 9472 input_1[0][0]
__________________________________________________________________________________________________
batch_normalization (BatchNorma (None, 75, 75, 64) 256 conv2d[0][0]
__________________________________________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 38, 38, 64) 0 batch_normalization[0][0]
__________________________________________________________________________________________________
conv2d_1 (Conv2D) (None, 38, 38, 64) 36928 max_pooling2d[0][0]
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 38, 38, 64) 256 conv2d_1[0][0]
__________________________________________________________________________________________________
conv2d_2 (Conv2D) (None, 38, 38, 64) 36928 batch_normalization_1[0][0]
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, 38, 38, 64) 256 conv2d_2[0][0]
__________________________________________________________________________________________________
add (Add) (None, 38, 38, 64) 0 batch_normalization_2[0][0]
max_pooling2d[0][0]
__________________________________________________________________________________________________
conv2d_3 (Conv2D) (None, 38, 38, 64) 36928 add[0][0]
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, 38, 38, 64) 256 conv2d_3[0][0]
__________________________________________________________________________________________________
conv2d_4 (Conv2D) (None, 38, 38, 64) 36928 batch_normalization_3[0][0]
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, 38, 38, 64) 256 conv2d_4[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, 38, 38, 64) 0 batch_normalization_4[0][0]
add[0][0]
__________________________________________________________________________________________________
conv2d_5 (Conv2D) (None, 38, 38, 64) 36928 add_1[0][0]
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, 38, 38, 64) 256 conv2d_5[0][0]
__________________________________________________________________________________________________
conv2d_6 (Conv2D) (None, 38, 38, 64) 36928 batch_normalization_5[0][0]
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, 38, 38, 64) 256 conv2d_6[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, 38, 38, 64) 0 batch_normalization_6[0][0]
add_1[0][0]
__________________________________________________________________________________________________
conv2d_7 (Conv2D) (None, 19, 19, 128) 73856 add_2[0][0]
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, 19, 19, 128) 512 conv2d_7[0][0]
__________________________________________________________________________________________________
conv2d_8 (Conv2D) (None, 19, 19, 128) 147584 batch_normalization_7[0][0]
__________________________________________________________________________________________________
conv2d_9 (Conv2D) (None, 19, 19, 128) 73856 add_2[0][0]
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, 19, 19, 128) 512 conv2d_8[0][0]
__________________________________________________________________________________________________
batch_normalization_9 (BatchNor (None, 19, 19, 128) 512 conv2d_9[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, 19, 19, 128) 0 batch_normalization_8[0][0]
batch_normalization_9[0][0]
__________________________________________________________________________________________________
conv2d_10 (Conv2D) (None, 19, 19, 128) 147584 add_3[0][0]
__________________________________________________________________________________________________
batch_normalization_10 (BatchNo (None, 19, 19, 128) 512 conv2d_10[0][0]
__________________________________________________________________________________________________
conv2d_11 (Conv2D) (None, 19, 19, 128) 147584 batch_normalization_10[0][0]
__________________________________________________________________________________________________
batch_normalization_11 (BatchNo (None, 19, 19, 128) 512 conv2d_11[0][0]
__________________________________________________________________________________________________
add_4 (Add) (None, 19, 19, 128) 0 batch_normalization_11[0][0]
add_3[0][0]
__________________________________________________________________________________________________
conv2d_12 (Conv2D) (None, 19, 19, 128) 147584 add_4[0][0]
__________________________________________________________________________________________________
batch_normalization_12 (BatchNo (None, 19, 19, 128) 512 conv2d_12[0][0]
__________________________________________________________________________________________________
conv2d_13 (Conv2D) (None, 19, 19, 128) 147584 batch_normalization_12[0][0]
__________________________________________________________________________________________________
batch_normalization_13 (BatchNo (None, 19, 19, 128) 512 conv2d_13[0][0]
__________________________________________________________________________________________________
add_5 (Add) (None, 19, 19, 128) 0 batch_normalization_13[0][0]
add_4[0][0]
__________________________________________________________________________________________________
conv2d_14 (Conv2D) (None, 19, 19, 128) 147584 add_5[0][0]
__________________________________________________________________________________________________
batch_normalization_14 (BatchNo (None, 19, 19, 128) 512 conv2d_14[0][0]
__________________________________________________________________________________________________
conv2d_15 (Conv2D) (None, 19, 19, 128) 147584 batch_normalization_14[0][0]
__________________________________________________________________________________________________
batch_normalization_15 (BatchNo (None, 19, 19, 128) 512 conv2d_15[0][0]
__________________________________________________________________________________________________
add_6 (Add) (None, 19, 19, 128) 0 batch_normalization_15[0][0]
add_5[0][0]
__________________________________________________________________________________________________
conv2d_16 (Conv2D) (None, 10, 10, 256) 295168 add_6[0][0]
__________________________________________________________________________________________________
batch_normalization_16 (BatchNo (None, 10, 10, 256) 1024 conv2d_16[0][0]
__________________________________________________________________________________________________
conv2d_17 (Conv2D) (None, 10, 10, 256) 590080 batch_normalization_16[0][0]
__________________________________________________________________________________________________
conv2d_18 (Conv2D) (None, 10, 10, 256) 295168 add_6[0][0]
__________________________________________________________________________________________________
batch_normalization_17 (BatchNo (None, 10, 10, 256) 1024 conv2d_17[0][0]
__________________________________________________________________________________________________
batch_normalization_18 (BatchNo (None, 10, 10, 256) 1024 conv2d_18[0][0]
__________________________________________________________________________________________________
add_7 (Add) (None, 10, 10, 256) 0 batch_normalization_17[0][0]
batch_normalization_18[0][0]
__________________________________________________________________________________________________
conv2d_19 (Conv2D) (None, 10, 10, 256) 590080 add_7[0][0]
__________________________________________________________________________________________________
batch_normalization_19 (BatchNo (None, 10, 10, 256) 1024 conv2d_19[0][0]
__________________________________________________________________________________________________
conv2d_20 (Conv2D) (None, 10, 10, 256) 590080 batch_normalization_19[0][0]
__________________________________________________________________________________________________
batch_normalization_20 (BatchNo (None, 10, 10, 256) 1024 conv2d_20[0][0]
__________________________________________________________________________________________________
add_8 (Add) (None, 10, 10, 256) 0 batch_normalization_20[0][0]
add_7[0][0]
__________________________________________________________________________________________________
conv2d_21 (Conv2D) (None, 10, 10, 256) 590080 add_8[0][0]
__________________________________________________________________________________________________
batch_normalization_21 (BatchNo (None, 10, 10, 256) 1024 conv2d_21[0][0]
__________________________________________________________________________________________________
conv2d_22 (Conv2D) (None, 10, 10, 256) 590080 batch_normalization_21[0][0]
__________________________________________________________________________________________________
batch_normalization_22 (BatchNo (None, 10, 10, 256) 1024 conv2d_22[0][0]
__________________________________________________________________________________________________
add_9 (Add) (None, 10, 10, 256) 0 batch_normalization_22[0][0]
add_8[0][0]
__________________________________________________________________________________________________
conv2d_23 (Conv2D) (None, 10, 10, 256) 590080 add_9[0][0]
__________________________________________________________________________________________________
batch_normalization_23 (BatchNo (None, 10, 10, 256) 1024 conv2d_23[0][0]
__________________________________________________________________________________________________
conv2d_24 (Conv2D) (None, 10, 10, 256) 590080 batch_normalization_23[0][0]
__________________________________________________________________________________________________
batch_normalization_24 (BatchNo (None, 10, 10, 256) 1024 conv2d_24[0][0]
__________________________________________________________________________________________________
add_10 (Add) (None, 10, 10, 256) 0 batch_normalization_24[0][0]
add_9[0][0]
__________________________________________________________________________________________________
conv2d_25 (Conv2D) (None, 10, 10, 256) 590080 add_10[0][0]
__________________________________________________________________________________________________
batch_normalization_25 (BatchNo (None, 10, 10, 256) 1024 conv2d_25[0][0]
__________________________________________________________________________________________________
conv2d_26 (Conv2D) (None, 10, 10, 256) 590080 batch_normalization_25[0][0]
__________________________________________________________________________________________________
batch_normalization_26 (BatchNo (None, 10, 10, 256) 1024 conv2d_26[0][0]
__________________________________________________________________________________________________
add_11 (Add) (None, 10, 10, 256) 0 batch_normalization_26[0][0]
add_10[0][0]
__________________________________________________________________________________________________
conv2d_27 (Conv2D) (None, 10, 10, 256) 590080 add_11[0][0]
__________________________________________________________________________________________________
batch_normalization_27 (BatchNo (None, 10, 10, 256) 1024 conv2d_27[0][0]
__________________________________________________________________________________________________
conv2d_28 (Conv2D) (None, 10, 10, 256) 590080 batch_normalization_27[0][0]
__________________________________________________________________________________________________
batch_normalization_28 (BatchNo (None, 10, 10, 256) 1024 conv2d_28[0][0]
__________________________________________________________________________________________________
add_12 (Add) (None, 10, 10, 256) 0 batch_normalization_28[0][0]
add_11[0][0]
__________________________________________________________________________________________________
conv2d_29 (Conv2D) (None, 5, 5, 512) 1180160 add_12[0][0]
__________________________________________________________________________________________________
batch_normalization_29 (BatchNo (None, 5, 5, 512) 2048 conv2d_29[0][0]
__________________________________________________________________________________________________
conv2d_30 (Conv2D) (None, 5, 5, 512) 2359808 batch_normalization_29[0][0]
__________________________________________________________________________________________________
conv2d_31 (Conv2D) (None, 5, 5, 512) 1180160 add_12[0][0]
__________________________________________________________________________________________________
batch_normalization_30 (BatchNo (None, 5, 5, 512) 2048 conv2d_30[0][0]
__________________________________________________________________________________________________
batch_normalization_31 (BatchNo (None, 5, 5, 512) 2048 conv2d_31[0][0]
__________________________________________________________________________________________________
add_13 (Add) (None, 5, 5, 512) 0 batch_normalization_30[0][0]
batch_normalization_31[0][0]
__________________________________________________________________________________________________
conv2d_32 (Conv2D) (None, 5, 5, 512) 2359808 add_13[0][0]
__________________________________________________________________________________________________
batch_normalization_32 (BatchNo (None, 5, 5, 512) 2048 conv2d_32[0][0]
__________________________________________________________________________________________________
conv2d_33 (Conv2D) (None, 5, 5, 512) 2359808 batch_normalization_32[0][0]
__________________________________________________________________________________________________
batch_normalization_33 (BatchNo (None, 5, 5, 512) 2048 conv2d_33[0][0]
__________________________________________________________________________________________________
add_14 (Add) (None, 5, 5, 512) 0 batch_normalization_33[0][0]
add_13[0][0]
__________________________________________________________________________________________________
conv2d_34 (Conv2D) (None, 5, 5, 512) 2359808 add_14[0][0]
__________________________________________________________________________________________________
batch_normalization_34 (BatchNo (None, 5, 5, 512) 2048 conv2d_34[0][0]
__________________________________________________________________________________________________
conv2d_35 (Conv2D) (None, 5, 5, 512) 2359808 batch_normalization_34[0][0]
__________________________________________________________________________________________________
batch_normalization_35 (BatchNo (None, 5, 5, 512) 2048 conv2d_35[0][0]
__________________________________________________________________________________________________
add_15 (Add) (None, 5, 5, 512) 0 batch_normalization_35[0][0]
add_14[0][0]
__________________________________________________________________________________________________
global_average_pooling2d (Globa (None, 512) 0 add_15[0][0]
__________________________________________________________________________________________________
dense (Dense) (None, 10) 5130 global_average_pooling2d[0][0]
==================================================================================================
Total params: 22,691,594
Trainable params: 22,674,570
Non-trainable params: 17,024
__________________________________________________________________________________________________